The Effects of Obesity on Joint Integrity and Mobility. A Cross-Sectional Anatomical Study
Bibliographic record
Abstract
Background: Obesity is a major global health problem resulting in a great deal of musculoskeletal disorders, most prominently joint degeneration and impaired mobility. Aims and Objectives: This study aimed and objective to assess the effect of obesity on joint integrity and mobility in Pakistani adults using radiographic and functional assessment. Method: A cross-sectional study was conducted at different tertiary healthcare centres in Lahore, Pakistan, among n=150 participants (30–60 years). Nonobese (BMI < 25 kg/m², n=75) and obese (BMI ≥ 30 kg/m², n=75) were categorized as the participants. X-rays and MRI were used to assess joint integrity (joint space narrowing, osteophyte formation, and subchondral sclerosis). Range of motion (ROM) assessments and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and functional limitations were used to evaluate mobility. Results: Joint degeneration was significantly higher in obese individuals, 60% showed joint space narrowing, 68% showed osteophyte formation, and 55% showed subchondral sclerosis (p < 0.001). Knee flexion, hip abduction, and ankle dorsiflexion were significantly reduced in the obese group by 18, 22, and 25%, respectively (p < 0.01). Obese participants had markedly higher WOMAC scores for pain (p < 0.001) and stiffness (p < 0.001) and lesser functional impairment (p < 0.001). Conclusion: obesity has a great negative effect on joint health, mobility, and functional capacity. Early weight management strategies, physiotherapy, and lifestyle modification are needed to avoid musculoskeletal complications of obesity. To decrease the burden of joint disorders, public health policies should focus on obesity prevention. Keywords: Obesity, Joint Integrity, Mobility Impairment, Osteoarthritis, Range of Motion, Musculoskeletal Disorders, Adipokines, Radiographic Assessment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".